Due to the uncertainty of many of the factors that influence the performance
of an emergency medical service, we propose using Bayesian networks
to model this kind of system. We use different algorithms for learning
Bayesian networks in order to build several models, from the hospital
manager's point of view, and apply them to the specific case of the
emergency service of a Spanish hospital. This first study of a real
problem includes preliminary data processing, the experiments carried
out, the comparison of the algorithms from different perspectives,
and some potential uses of Bayesian networks for management problems
in the health service.
%0 Journal Article
%1 Acid2004
%A Acid, Silvia
%A de Campos, Luis M.
%A Fern�ndez-Luna, Juan M.
%A Rodr�guez, Susana
%A Rodr�guez, Jos� Mar�a
%A Salcedo, Jos� Luis
%D 2004
%J Artificial Intelligence in Medicine
%K Bayesian networks
%N 3
%P 215 - 232
%R DOI: 10.1016/j.artmed.2003.11.002
%T A comparison of learning algorithms for Bayesian networks: a case
study based on data from an emergency medical service
%U http://www.sciencedirect.com/science/article/B6T4K-4BM90XX-1/2/306cb5b02d78bc4fedca6044efcf2ee0
%V 30
%X Due to the uncertainty of many of the factors that influence the performance
of an emergency medical service, we propose using Bayesian networks
to model this kind of system. We use different algorithms for learning
Bayesian networks in order to build several models, from the hospital
manager's point of view, and apply them to the specific case of the
emergency service of a Spanish hospital. This first study of a real
problem includes preliminary data processing, the experiments carried
out, the comparison of the algorithms from different perspectives,
and some potential uses of Bayesian networks for management problems
in the health service.
@article{Acid2004,
abstract = {Due to the uncertainty of many of the factors that influence the performance
of an emergency medical service, we propose using Bayesian networks
to model this kind of system. We use different algorithms for learning
Bayesian networks in order to build several models, from the hospital
manager's point of view, and apply them to the specific case of the
emergency service of a Spanish hospital. This first study of a real
problem includes preliminary data processing, the experiments carried
out, the comparison of the algorithms from different perspectives,
and some potential uses of Bayesian networks for management problems
in the health service.},
added-at = {2009-09-12T19:19:34.000+0200},
author = {Acid, Silvia and de Campos, Luis M. and Fern�ndez-Luna, Juan M. and Rodr�guez, Susana and Rodr�guez, Jos� Mar�a and Salcedo, Jos� Luis},
biburl = {https://www.bibsonomy.org/bibtex/211ff26c0f0ddbe92c85e746815175175/mozaher},
doi = {DOI: 10.1016/j.artmed.2003.11.002},
file = {:Acid2004.pdf:PDF},
interhash = {d1b269617f40142f5023ad4efe521109},
intrahash = {11ff26c0f0ddbe92c85e746815175175},
issn = {0933-3657},
journal = {Artificial Intelligence in Medicine},
keywords = {Bayesian networks},
note = {Bayesian Networks in Biomedicince and Health-Care},
number = 3,
owner = {Mozaherul Hoque},
pages = {215 - 232},
timestamp = {2009-09-12T19:19:36.000+0200},
title = {A comparison of learning algorithms for Bayesian networks: a case
study based on data from an emergency medical service},
url = {http://www.sciencedirect.com/science/article/B6T4K-4BM90XX-1/2/306cb5b02d78bc4fedca6044efcf2ee0},
volume = 30,
year = 2004
}